Identification of potential land cover changes on a continental scale using NDVI time-series from SPOT VEGETATION

• Tipo: Artigo em Revista Científica Internacional
• Data: 2013

Autores

Arlete Rodrigues (Autor) Outra; Andre R S Marcal (Autor) FCUP; Mario Cunha (Autor) FCUP

Revista

Título: International Journal of Remote Sensing

Vol. 34

Páginas: 8028-8050

ISSN: 0143-1161

Editora: Taylor & Francis

Indexação

ISI Web of Knowledge - 14 Citações

Scopus - 18 Citações

Classificação Científica

FOS: Ciências da engenharia e tecnologias > Engenharia do ambiente

Outras Informações

ID Authenticus: P-006-686

DOI: 10.1080/01431161.2013.828184

Abstract (EN): The identification of land cover changes on a continental scale is a laborious and time-consuming process. A new methodology is proposed based exclusively on SPOT VGT data, illustrated for the African Continent using GLC2000 as reference to select 26 distinct land cover types (classes). For each class, the normalized difference vegetation index (NDVI) time-series are extracted from SPOT VGT images and a hierarchical aggregation is done using two different methods: one that preserves the initial signatures throughout the hierarchical process, and another that recalculates the signatures for each aggregation level. The average classification agreement was above 89% using 26 classes. Reducing the number of classes improves classification agreement. In order to study the influence of temporal variability in the classification results, the methodology was applied on data from 1999, 2001, 2008, and 2010. With 26 classes, the best average classification agreement obtained was 94.5% with annual data, against 74.1% with interannual data.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 23